(1)负责或作为骨干人员参与研发过30余项国家重点项目和国际合作项目,获得国家教育部(委)、科技部(委)、北京市各类奖励10余次。
(2)在国内外知名刊物和学术会议上发表了310余篇学术论文,其中有13篇(第一作者3篇)获优秀论文奖;出版专著14本。代表性论文如下:
[1] Tongxu Li, Hui Zhang, Thomas Fang Zheng, “The Voiceprint Recognition Technology and Its Applications in Unsupervised Identity Authentication,” 8(9): 46-54, 2018, Chinese Association for Artificial Intelligence Transactions (in Chinese)
[2] Lantian Li, Dong Wang, Chenhao Zhang, and Thomas Fang Zheng, "Improving short utterance speaker recognition by modeling speech unit classes," IEEE/ACM Trans. on Audio, Speech, and Language Processing, pp. 1129-1139, vol. 24, no. 6, June 2016
[3] Linlin Wang, Jun Wang, Lantian Li, Thomas Fang Zheng, Frank K. Soong, “Improving speaker verification performance against long-term speaker variability,” Speech Communication, 79 (2016), 14-29, Mar. 2016
[4] Miao Fan, Qiang Zhou, Thomas Fang Zheng, Ralph Grishman. “Distributed Representation Learning for Knowledge Bases with Entity Descriptions,” Pattern Recognition Letters, DOI: 10.1016/j.patrec.2016.09.005, Elsevier.
[5] Miao Fan, Qiang Zhou, Andrew Abel, Thomas Fang Zheng, Ralph Grishman, “Probabilistic Belief Embedding for Large-Scale Knowledge Population,” Cognitive Computation, December 2016, Volume 8, Issue 6, pp. 1087-1102
[6] Meng Sun, Xiongwei Zhang, Hugo Van hamme, and Thomas Fang Zheng, "Unseen noise estimation using separable deep auto encoder for speech enhancement," IEEE/ACM Transactions on Audio, Speech, and Language Processing, pp. 93-104, Vol. 24, No. 1, Jan. 2016 (DOI 10.1109/TASLP.2015.2498101)
[7] Guoyu Tang, Yunqing Xia, Erik Cambria, Peng Jin, Thomas Fang Zheng, “Document representation with statistical word senses in cross-lingual document clustering,” Vol. 29, No. 2 (2015), International Journal of Pattern Recognition and Artificial Intelligence, World Scientific Publishing Company
[8] Shi Yin, Chao Liu, Zhiyong Zhang, Yiye Lin, Dong Wang, Javier Tejedor, Thomas Fang Zheng and Yingguo Li, “Noisy Training for Deep Neural Networks in Speech Recognition,” EURASIP Journal on Audio, Speech, and Music Processing, 2015, 2015:2
[9] Dong Wang, Ravichander Vipperla, Nicholas Evans, Thomas Fang Zheng, “Online Non-Negative Convolutive Pattern Learning for Speech Signals,” IEEE Trans. on Signal Processing, 61(1): 44-56, Jan. 1, 2013
[10] Mijit Ablimit, Sardar Parhat, Askar Hamdulla, Thomas Fang Zheng, “Multilingual Stemming and Term Extraction for Uyghur, Kazak and Kirghiz,” the 10th APSIPA Annual Summit and Conference (APSIPA ASC 2018), November 12-15, 2018, 587-590, Hawaii, USA
[11] Thomas Fang Zheng, “Speech Signal for Unsupervised Identity Authentication,” APSIPA 10th Anniversary Magazine, pp. 26-28, Nov. 2018, Hawaii, USA
[12] Lantian Li, Zhiyuan Tang, Dong Wang, Thomas Fang Zheng, “Full-Info Training for Deep Speaker Feature Learning,” International Conference on Acoustics, Speech and Signal Processing (ICASSP’18), pp. 5369-5373, Apr. 15-20, 2018, Calgary, Alberta, Canada
[13] Lantian Li, Dong Wang, Yixiang Chen, Ying Shi, Zhiyuan Tang, Thomas Fang Zheng, “Deep Factorization for Speech Signal,” International Conference on Acoustics, Speech and Signal Processing (ICASSP’18), pp. 5094-5098, Apr. 15-20, 2018, Calgary, Alberta, Canada
[14] Xingliang Cheng, Xiaotong Zhang, Mingxing Xu, and Thomas Fang Zheng, “MMANN: Multimodal Multilevel Attention Neural Network for Horror Clip Detection,” the 10th APSIPA Annual Summit and Conference (APSIPA ASC 2018), November 12-15, 2018, 329-334, Hawaii, USA
[15] Xiaotong Zhang, Xingliang Cheng, Mingxing Xu, Thomas Fang Zheng, “Imbalance Learning-based Framework for Fear Recognition in the MediaEval Emotional Impact of Movies Task,” pp.3678-3682, Interspeech 2018, 2-6 Sepember 2018, Hyderabad, India, DOI: 10.21437/Interspeech.2018-1744
[16] Replay Detection using CQT-based Modified Group Delay Feature and ResNeWt Network in ASVspoof 2019
[17] XIAOLONG WU, CHANG FENG, MINGXING XU, THOMAS FANG ZHENG, ASKAR HAMDULLA,“DialoguePCN: Perception and Cognition Network for Emotion Recognition in Conversations”,IEEE Access, VOLUME 11, pp. 141251-141260, 2023, DOI 10.1109/ACCESS.2023.3342456
著作:《Robustness-Related Issues in Speaker Recognition》
(3)拥有16项发明专利(包括一项国际发明专利)和1项实用新型专利。近年所获代表性专利如下:
[1] 基于分布式神经网络的语言模型训练方法及其系统、2014100679169、2014.02.27、中国
[2] 语音密码的认证方法及系统、2017100532098、2017.01.22、中国
[3] 基于动态密码语音的身份确认系统及方法、ZL 201310123555.0、2013.10.12、中国
[4] 一种基于动态数字验证码的语音门禁系统、ZL 201620119381.X、2016、中国
[5] 声纹模型自动重建的方法和装置、ZL 201510061721.8、2015.10.06、中国
[6] 指纹与声纹双认证方法、ZL 201510047966.5、2015.10.04、中国
[7] 一种用于语音重放检测的特征提取方法及装置、ZL201810191512.9、中国
(4)《基于动态密码语音的无监督身份认证系统》通过中国电子学会科技成果鉴定,鉴定结论是“整体处于国际领先水平”。